{"about":{"site":"https://codewithpapers.app","non_affiliation":"Code with Papers and Syntology are not affiliated with, endorsed by, or sponsored by Papers with Code, Meta, or the pwc-archive mirror.","licence":"CC BY-SA 4.0","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","attribution":"https://codewithpapers.app/attribution","modified":"archive material modified by Syntology; see the attribution page"},"url":"/paper/graph-sparse-logistic-regression","title":"Graph-Sparse Logistic Regression","arxiv_id":"1712.05510","date":"2017-12-15","proceeding":null,"authors":["Alexander LeNail","Ludwig Schmidt","Johnathan Li","Tobias Ehrenberger","Karen Sachs","Stefanie Jegelka","Ernest Fraenkel"],"abstract":"We introduce Graph-Sparse Logistic Regression, a new algorithm for\nclassification for the case in which the support should be sparse but connected\non a graph. We val- idate this algorithm against synthetic data and benchmark\nit against L1-regularized Logistic Regression. We then explore our technique in\nthe bioinformatics context of proteomics data on the interactome graph. We make\nall our experimental code public and provide GSLR as an open source package.","url_abs":"http://arxiv.org/abs/1712.05510v1","url_pdf":"http://arxiv.org/pdf/1712.05510v1.pdf","source":{"archive":"pwc-archive (Hugging Face), CC BY-SA 4.0","snapshot":"2025-07-28","licence_url":"https://creativecommons.org/licenses/by-sa/4.0/legalcode","row_kind":"abstracts"},"code_links":[{"paper_slug":"graph-sparse-logistic-regression","repo_url":"https://github.com/fraenkel-lab/GSLR","is_official":1,"mentioned_in_paper":1,"mentioned_in_github":1,"framework":"none","reach":null}],"tasks":[{"task_slug":"classification","task_name":"General Classification"},{"task_slug":"regression-1","task_name":"regression"}],"methods":[{"method_slug":"logistic-regression","method_name":"Logistic Regression"}],"datasets_introduced":[],"methods_introduced":[],"results":[],"syntology":{"atlas_url":null,"mcp":null,"developers":"https://syntology.ai/developers"},"arxiv_metadata":null,"syntology_extracted_results":null}